Modern information technology has allowed for an unprecedented level of data collection and analysis. This has catalyzed substantial developments in the private and public sectors; specifically, the proliferation of Big Data and/or increasingly larger data sets has allowed for the sophistication of predictive analytics, interaction with customers, risk analysis and sustainable urban planning. However, acquiring this data and performing adequate analysis is often extremely costly and necessitates advanced infrastructure and highly skilled experts. Additionally, despite the great effort afforded to Big Data, it can often be plagued with human generated errors originating from inaccurately recording data or recording it inconsistently as well as faulty assumptions of correlation which can lead to inaccurate analysis of inputted data.
A prominent source of inaccuracy in modern information originates from the human and computer data entry process. Specifically, it has been found that approximately 7.4% of all clerical and financial data entered into computer systems is done so erroneously. Additionally, this issue is further compounded as human performed data entry often lacks consistency and homogeneity. Specifically, those performing data entry often record the same or similar data points in dissimilar ways. For example, this can occur when two employees performing data entry record a client's name differently; such as, first name followed by last name verse last name followed by first name. This can translate to a significant disadvantage when making decisions based on data which at some point was entered into a system via human performed data entry.
Similarly, another source of these inaccuracies arises when machines and/or computers are used to read, record, calculate and/or transpose data and figures into a corresponding program or computer system. The nature of these errors arise as machines and computers must be designed and maintained by human engineers or scientists who are themselves prone to error. In the event that the coding or designing assumptions are flawed, an inaccurate program could be created which could lead to the contamination of data and subsequently, create incorrect information. As computers and machines can conduct simple data entry and calculations at extremely fast rates, huge sets of data could be incorrectly recorded and if not appropriately stored or backed up, valuable and perhaps irreplaceable, data could be lost or damaged beyond repair. Similarly, interpreters of data can engage in faulty assumptions of correlation which can lead to the incorrect interpretation of analyzed data. Specifically, these errors occur when a corollary relationship existing between data points or sets is mistaken as an implication of causation between said data points or sets. Errors of this type can result in a multitude of analysis issues such as an insufficient understanding of the true relationship between two or more sets of data or a misunderstanding of the cause and effect between two or more variables.
Additionally, computers and machines as they are presently commercially available often lack the ability to solve even simple problems which require critical thinking or ingenuity. An example would be a computer program designed to input accounting expenses into the general ledger and one of the expenses to be inputted is actually a cost of goods sold. A human inputting this data, with even an elementary understanding of accounting, would identify this error and remedy it. As such, even the most automated computer generated data entry can lead to substantial error when the data being supplied is not entirely free of potential problems which might require critical thinking or ingenuity to solve, such as how to handle mislabeled files.
In speaking to the errors generated by human performed data entry, one solution is to reduce the error rate and inconsistencies associated with data entry by training employees in data entry best practices. However, employee training can often be a costly course of action which does not yield long term benefits for the company. Specifically, individuals who receive training become more highly skilled and are therefore more competitive in the job market. As such, they may find alternate employment with higher pay or other advantages like an office location closer to their home. Ultimately, training is often a disadvantageous option when searching for solutions to lower the error rate and increase consistency or homogeneity of human generated data entry.
In speaking to the errors generated by computers or machines during automated data entry, a solution exists. According to many skilled in the art, improving the accuracy of data entry can be accomplished by limiting human interaction and dependence in this process. As such, machines or computers should be used to read, record, calculate and/or transpose data and figures into appropriate fields which leads to the creation of information. However, if the data entry or analysis program is designed with faulty assumptions, coding errors or data organization which requires critical thinking, the data entry and subsequent information created cannot be treated as correct.
The nature of these two solutions shows an interdependency of failure which impacts the public and private sectors. Human performed data entry and analysis design is often times inaccurate above acceptable error rates due to inaccurate or inconsistent data entry while machines and/or computers cannot solve even basic problems which often arise during data entry. As such, the inventors has determined that the most optimal way to solve this problem is by designing an electronic system to address this granular data entry problem.
The following description is presented to enable any person skilled in the art to make and use the invention, and is provided in the context of several particular applications and their requirements. Various modifications to the disclosed embodiments will be readily apparent to those skilled in the art, and the general principles defined herein may be applied to other embodiments and applications without departing from the spirit and scope of the present invention. Thus, the present invention is not limited to the embodiments shown, but is to be accorded the widest scope consistent with the principles and features disclosed herein.
Additional objects and advantages of the disclosed embodiments will be set forth in the description which follows, and in part will be obvious from the description, or may be learned from the practice of the disclosed embodiments.